Java 类名:com.alibaba.alink.operator.stream.dataproc.StratifiedSampleStreamOp
Python 类名:StratifiedSampleStreamOp
功能介绍
分层采样是对每个类别进行随机抽样。
参数说明
| 名称 | 中文名称 | 描述 | 类型 | 是否必须? | 取值范围 | 默认值 | | —- | —- | —- | —- | —- | —- | —- |
| strataCol | 分层列 | 分层列 | String | ✓ | | |
| strataRatios | 采用比率 | 采用比率, eg, a:0.1,b:0.3 | String | ✓ | | |
| strataRatio | 采用比率 | 采用比率 | Double | | | -1.0 |
代码示例
Python 代码
from pyalink.alink import *
import pandas as pd
useLocalEnv(1)
df_data = pd.DataFrame([
['a',0.0,0.0],
['a',0.2,0.1],
['b',0.2,0.8],
['b',9.5,9.7],
['b',9.1,9.6],
['b',9.3,9.9]
])
streamData = StreamOperator.fromDataframe(df_data, schemaStr='x1 string, x2 double, x3 double')
sampleStreamOp = StratifiedSampleStreamOp()\
.setStrataCol("x1")\
.setStrataRatios("a:0.5,b:0.5")
sampleStreamOp.linkFrom(streamData).print()
StreamOperator.execute()
Java 代码
import org.apache.flink.types.Row;
import com.alibaba.alink.operator.stream.StreamOperator;
import com.alibaba.alink.operator.stream.dataproc.StratifiedSampleStreamOp;
import com.alibaba.alink.operator.stream.source.MemSourceStreamOp;
import org.junit.Test;
import java.util.Arrays;
import java.util.List;
public class StratifiedSampleStreamOpTest {
@Test
public void testStratifiedSampleStreamOp() throws Exception {
List <Row> df_data = Arrays.asList(
Row.of("a", 0.0, 0.0),
Row.of("a", 0.2, 0.1),
Row.of("b", 0.2, 0.8),
Row.of("b", 9.5, 9.7),
Row.of("b", 9.1, 9.6),
Row.of("b", 9.3, 9.9)
);
StreamOperator <?> streamData = new MemSourceStreamOp(df_data, "x1 string, x2 double, x3 double");
StreamOperator <?> sampleStreamOp = new StratifiedSampleStreamOp()
.setStrataCol("x1")
.setStrataRatios("a:0.5,b:0.5");
sampleStreamOp.linkFrom(streamData).print();
StreamOperator.execute();
}
}
运行结果
| x1 | x2 | x3 | | —- | —- | —- |
| b | 9.3 | 9.9 |
| a | 0.0 | 0.0 |
| b | 0.2 | 0.8 |